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8:58
YouTube
Quinn Wang
Hyperparameter Tuning in Machine Learning | Grid Search | How it Works and Sklearn Implementation
This series is going to focus on one important aspect of ML, hyperparameter tuning. In this video we are going to talk about grid search, including what it is and how to use the scikit-learn GridSearchCV module. In the module, we are going to dive into some important fields that you might want to customize, instead of just using the default ...
11.1K views
May 8, 2020
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Bayesian optimization is a method used to optimize complex functions that are expensive or time-consuming to evaluate. It is widely applied in machine learning, engineering, and scientific research to improve efficiency and precision, particularly in scenarios like hyperparameter tuning and experimental design. ✔️ Efficient Function Evaluation: Bayesian optimization minimizes costly evaluations, making it ideal for scenarios where each evaluation has a high resource cost. ✔️ Versatility: It hand
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